46. Table 1.3 lists the ages and weights of nine girls.TABLE 1.3 Girls' Ages and WeightsAge (months)Weight (pounds)221923212425272829313128343238344339(a) Find the linear regression equation for the data.(b) Find the slope of the regression line. What does the sloperepresent?(c) Superimpose the graph of the linear regression equation on ascatter plot of the data.(d) Use the regression equation to predict the approximateweight of a 30-month-old girl..

NOTE:- WE HAVE SOLVED FIRST THREE PARTS OF THE QUESTION AS PER BARTLEBY GUIDELINES. KINDLY REPOST…

Answered: 46. Table 1.3 lists the ages and…

Calculus: Early Transcendentals

8th Edition

ISBN:9781285741550

Author:James Stewart

Publisher:James Stewart

Chapter1: Functions And Models

Section: Chapter Questions

Problem 1RCC: (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How...

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Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x Test score, y 5. 72 (a) x=4 hours (c) x= 13 hours (b) x=25 hours (d) x=1.5 hours 38 43 51 48 64 Find the regression equation. (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
c. What are the 2 main pieces of information you get from the linear regression model? Should I go back to the data set and recalculate slope and y intercept if I already have determined the equation of the trend line?
7. Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. The table shows the shoe size and heights (in.) for 6 men. Shoe size, x Height, y 6.0 65.5 7.0 68.5 9.0 12.0 12.5 74.5 13.0 72.5 70.5 73.5 Find the regression equation. y = (Round to three decimal places as needed.) X+ Choose the correct graph below. O A. OB. OC. OD. 75- 75- 14 Shoe size Shoe size Shoe size Shoe size Height(in.) Height (in.) Height(in.)
A graphing calculator is recommended. When laboratory rats are exposed to asbestos fibers, some of them develop lung tumors. The table lists the results of several experiments by different scientists. Asbestos exposure (fibers/mL) y = 50 Mice with Tumors (%) 400 O 500 900 1,100 1,600 1,800 2,000 3,000 3000 2500 2000 1500 (a) Find the regression line for the data. (Use x for asbestos exposure in fibers/mL and y for percent of mice with tumors. Round your values to four decimal places.) 1000 500 Percent of mice that develop lung tumors (b) Construct a scatter plot and graph the regression line. o 0 7 6 11 10 27 41 38 37 49 20 30 40 50 Asbestos Exposure (Fibers/mL.) 60 Mice with Tumors (%) 3000 ● 2500 2000 1500 1000 500 60 0 0 10 20 30 40 50 60 Asbestos Exposure (Fibers/mL) Ⓡ 4
A. run a simple regression- dependent variable is Weeks, independent variable is Age. B. run a multiple regression with dependent variable weeks and independent variable-age, married, head, manager and sales. C. Create the regular and standardized residual plots for both. Please show the tables when entering values of the regression for both the outputs and the scatter plots.
Demand for Smartphones The following table shows worldwide sales of a type of phone and their average selling prices in 2012, 2013, and 2017. Year 2012 2013 2017 Selling Price p ($100) 4 3 2 Sales q (billions) 0.7 1 2 Find the regression line (round coefficients to one decimal place). q(p) = Use the regression line to estimate the demand (in millions of units sold) when the selling price was $350. million
Find the equation of the regression line for given data
The tables show the amount of revenue (y) in billions for different companies x years after 2005. Match the table with the correct description of its regression model and correlation. Negative Linear Regression 1. a0 1 2 3 4 5 6 78 9 10 Strong Negative Correlation y 12 12 13 14 15 16 18 19 21 22 25 Positive Linear Regression * 0 1 2 3 4 5 6 7 89 10 y 20 18 17 15 13 14 16 18 21 25 28 2. Strong Positive Correlation Quadratic Regression * 0123 4 5 6 7 8 9 10 3. Strong Positive Correlation y 5679 13 15 18 24 25 28 30 Increasing Exponential Regression 4. x0 1 2 3 4 5 6 789 10 Strong Positive Correlation y 20 20 19 18 16 15 12 8765 Decreasing Exponential Regression z0 1 2 3 4 5 6 7 8 9 10 5. Strong Negative Correlation y 20 19 20 18 16 15 13 11 10 11 10
Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative? A. The slope is negative. As the independent variable increases the dependent variable also tends to increase. B. The slope is negative. As the independent variable increases the dependent variable tends to decrease. C. The slope is positive. As the independent variable increases the dependent variable also tends to increase. D. The slope is positive. As the independent variable increases the dependent variable tends to decrease.
Oil Recovery A U.S. state's Bureau of Economic Geology published a study on the economic impact of using carbon dioxide enhanced oil recovery (EOR) technology to extract additional oil from fields that have reached the end of their conventional economic life. The following table gives the approximate number of jobs for the citizens that would be created at various levels of recovery. Percent Recovery (%) 20 Jobs Created (Millions) Find the regression line. ()-0.135x+5.15 x Need Help? Submit Answer Use the regression line to estimate the number of jobs (in millions) that would be created at a recovery level of 70%. x million jobs Read It 8 Watch It 40 80 100 11 14 20
why the correct answer is letter b?
A manager wishes to determine the relationship between the number of years her sales representatives have been employed by the firm and their amount of sales (in thousands of dollars) per month. Find the equation of the regression line for the given data.

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